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operationalizing

The challenges for modern marketers in their effort to create a delightful customer experience vary from the sheer volume of digital channels to organizing and operationalizing the data they create. Add to that siloed team structures both within departments and cross-functionally and before long marketers begin to scoff at “challenge” and begin to think “impossible”.

This TDWI Best Practices Report focuses on how organizations can and are operationalizing analytics to derive business value. It provides in-depth survey analysis of current strategies and future trends for embedded analytics across both organizational and technical dimensions, including organizational culture, infrastructure, data and processes. It looks at challenges and how organizations are overcoming them, and offers recommendations and best practices for successfully operationalizing analytics in the organization.

Every day, companies generate mountains of data that are critical to their business. With that data comes
a clear challenge: How do you protect exabytes of data that's strewn across global data centers,
computer rooms, remote offices, laptops, desktops, and mobile devices, as well as hosted by many
different cloud providers, without choking business agility, employee productivity, and customer
experience? The solution lies not in throwing more technology at the network, but in taking specific steps
to identify malicious actions and respond to them in order to fix the issue, a process known as
operationalizing security.

Navigating Uncertainty & Disruption in a Post-Brexit World
Risk management and finance professionals are navigating an unprecedented period of uncertainty. In a post-Brexit world, how can business leaders best navigate disruption?
Data has become the most valuable business commodity, but not all data is meaningful. Data that helps you uncover hidden associations with customers, partners and suppliers can be a true catalyst for business transformation and growth.
In this ebook, we have mapped out the crucial steps in the journey towards operationalizing relationship data to:
- Define Relationship Data
- Use relationship data to unlock new opportunities
- Apply relationship data across the organization to drive growth

Wikibon conducted in-depth interviews with organizations that had achieved Big Data success and high rates of returns. These interviews determined an important generality: that Big Data winners focused on operationalizing and automating their Big Data projects. They used Inline Analytics to drive algorithms that directly connected to and facilitated automatic change in the operational systems-of-record. These algorithms were usually developed and supported by data tables derived using Deep Data Analytics from Big Data Hadoop systems and/or data warehouses. Instead of focusing on enlightening the few with pretty historical graphs, successful players focused on changing the operational systems for everybody and managed the feedback and improvement process from the company as a whole.

It’s not easy being today’s CISO or CIO. With the advent of cloud computing, Shadow IT, and mobility, the risk surface area for enterprises has increased dramatically, while IT budgets have shrunk and skilled cyber security talent is virtually impossible to find.
Thankfully, the CIS Top 20 Critical Controls provides a pragmatic approach, offering prioritized guidance on the important steps for implementing basic cyber hygiene practices. With the CIS Top 20 Critical Security Controls, CISOs now have a blueprint for reducing risk and managing compliance.
By automating each of these controls, CISOs enable their information security teams to do much more with less, essentially operationalizing good cyber hygiene.

Once you've designed and secured your Global Transit Network, are you done? Are you ready to hand day-to-day responsibility over to an operations team? Or, are there other elements you need to ensure that the day-to-day operation of your transit hub is efficient and effective?
As part of our fact-filled AWS Bootcamp series, Aviatrix CTO Sherry Wei and Neel Kamal, head of field operations at Aviatrix, demonstrate the best practices they've gleaned from working with operations teams, all who require:
• Visibility: Do you have a way to centrally view your network, see performance bottlenecks, control security policies, and set other configuration details?
• Deep Analytics: Can you easily gather performance and audit data and export it to Splunk, DataDog, or other advanced reporting tools?
• Monitoring and Troubleshooting: Do you have a real-time view of network health, and how easily can you access the data needed to locate and fix issues?
• Alert Management: When issues do occur, what r

The focus of SDN is on transforming the network to support applications and meet the expectations of users and businesses that rely on them. Scaling modern networks is challenging due to the explosive growth of compute, network, and application resources-combined with increased mobility of apps migrating to the cloud and users across multiple devices. As an approach to operationalizing the network, SDN enables organizations to achieve greater economies of operational scale through the use of APIs to automate and orchestrate the network, as well as the application services that support applications. Read this whitepaper to learn how applications are driving new requirements for both businesses and networks that require disruptive, radical change.

The potential for analytics to transform health care – to make it more personalized, intelligent, cost-efficient and effective – is immense. The question is, how will you move your organization forward to exploit the power of analytics? In this paper, explore recommendations and best practices from experts at UnitedHealth Group, Eli Lilly and Company, and Mercy Virtual who are operationalizing SAS analytics across their enterprises and realizing impressive results.

Behind the vast majority of legitimate alerts sent to the IT security team is an attacker who exploits multiple attack techniques to infiltrate your infrastructure and compromise your critical data and systems. Targeted multi-phased attacks include a series of cyber attack chain steps: recognition, vulnerability analysis, operation and, finally, exfiltration of critical business data.

Behind the vast majority of legitimate alerts sent to the IT security team is an attacker who exploits multiple attack techniques to infiltrate your infrastructure and compromise your critical data and systems. Targeted multi-phased attacks include a series of cyber attack chain steps: recognition, vulnerability analysis, operation and, finally, exfiltration of critical business data.

Read this white paper to learn about guidance to operationalize security and put the top 10 best SIEM practices to work, offering pertinent insights and details about how to gain more assure value from security information and event management.

Every day, companies generate mountains of data that are critical to their business. With that data comes
a clear challenge: How do you protect exabytes of data that's strewn across global data centers,
computer rooms, remote offices, laptops, desktops, and mobile devices, as well as hosted by many
different cloud providers, without choking business agility, employee productivity, and customer
experience? The solution lies not in throwing more technology at the network, but in taking specific steps
to identify malicious actions and respond to them in order to fix the issue, a process known as
operationalizing security.

The solution to operationalizing analytic s involves the effective combination of a Decision Management approach with a robust, modern analytic technology platform. This paper discusses both how to use a focus on decisions to ensure the right problem gets solved and what such an analytic technology platform looks like.

You may know some data management basics, but are you aware of the transformational results that can result from doing data management right? This paper explains core data management capabilities, then describes how a solid data management foundation can help you get more out of your data.
Fraudsters are only becoming smarter. How is your organization keeping pace and staying ahead of fraud schemes and regulatory mandates to monitor for them? In this e-book, learn the basics in how to prevent fraud, achieve compliance and preserve security.

As the pace of business continues to accelerate, forward-looking organizations are beginning to
realize that it is not enough to analyze their data; they must also take action on it. To do this, more
businesses are beginning to systematically operationalize their analytics as part of a business process.
Operationalizing and embedding analytics is about integrating actionable insights into systems and
business processes used to make decisions. These systems might be automated or provide manual,
actionable insights. Analytics are currently being embedded into dashboards, applications, devices,
systems, and databases. Examples run from simple to complex and organizations are at different
stages of operational deployment. Newer examples of operational analytics include support for
logistics, customer call centers, fraud detection, and recommendation engines to name just a few.
Embedding analytics is certainly not new but has been gaining more attention recently as data
volumes and the freq

Virtualization caused a major cultural shift in IT. By enabling physical assets to be better utilized, IT teams realized that they could deliver systems to their customers in a more timely manner, thereby delivering better value. In this webinar you will learn what is NetOps and how is it different from DevOps.

Ziff Davis recently surveyed over 300 IT professionals on the state of big data and analytics initiatives in their organizations. The results tell a compelling story: while most IT pros understand the value of big data, actually operationalizing their analytics strategies to deliver usable insights to their organizations remains a challenge.

When Information Revolution1 was published in 2006, no Chinese based companies were among the top 10 largest companies by market capitalization. Apple didn’t sell phones. Facebook was something college kids used to connect with their friends. Back then, we talked a lot about the amount of data coming in and faster processing speed.
What we believed then remains true today: Data, and the decision-making process, can be moved throughout the organization to equip every decision maker (automated, line worker, analyst, executive) to make the best choices. By operationalizing analytics, organizations can identify and quantify both opportunity and risk. Information Revolution highlighted SAS’ Information Evolution Model, which helps organizations understand how they interact with their information and how to extract more value from it through analytics.

This TDWI Best Practices Report focuses on how organizations can and are operationalizing analytics to derive business value. It provides in-depth survey analysis of current strategies and future trends for embedded analytics across both organizational and technical dimensions, including organizational culture, infrastructure, data and processes. It looks at challenges and how organizations are overcoming them, and offers recommendations and best practices for successfully operationalizing analytics in the organization.

In this paper you’ll learn five steps to implement and maintain PCI DSS compliance at your organization by:
Determining your true business requirements
Inventorying locations and assets
Segmenting environments
Operationalizing controls
Automating controls and control reporting
Demonstrating compliance with PCI DSS is far from a trivial exercise.
This checklist will help you on your quest to achieve and maintain PCI DSS compliance.

Maintaining Payment Card Industry Data Security Standard (PCI DSS) compliance can be both difficult and expensive. For most small to medium sized organizations, it doesn’t have to be as long as you have the right plan and tools in place. In this paper you’ll learn five steps to implement and maintain PCI DSS compliance at your organization by:
• Determining your true business requirements
• Inventorying locations and assets
• Segmenting environments
• Operationalizing controls
• Automating controls and control reporting
Demonstrating compliance with PCI DSS is far from a trivial exercise. This checklist will help you on your quest to achieve and maintain PCI DSS compliance.

As the pace of business continues to accelerate, forward-looking organizations are beginning to realize that it is not enough to analyze their data; they must also take action on it. To do this, more businesses are beginning to systematically operationalize their analytics as part of a business process. Operationalizing and embedding analytics is about integrating actionable insights into systems and business processes used to make decisions. These systems might be automated or provide manual, actionable insights. Analytics are currently being embedded into dashboards, applications, devices, systems, and databases. Examples run from simple to complex and organizations are at different stages of operational deployment.

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